×

Close

Type:
**Note**Institute:
**
Sreenivasa Institute of Technology and Management Studies
**Course:
**
B.Tech
**Specialization:
**Computer Science Engineering**Offline Downloads:
**114**Views:
**7578**Uploaded:
**3 months ago**Add to Favourite

Touch here to read

Page-1

Topic:

SITAMS – B.Tech – III Year - II Sem CSE
13CSE 321 – Theory of Computation
Dr. D. Jagadeesan, B.E., M.Tech., Ph.D.,
Professor in CSE,
Unit – I
Syllabus : Unit – I : FINITE AUTOMATA
Introduction- Strings - Alphabets and languages - Finite state automata – Basic Definitions Deterministic finite automata – Non deterministic finite automata - Equivalence of DFA’s and
NFA’s - Finite automata with output – More machines and mealy machines - Minimization of FA Equivalence between two FA’s - NFA with ε –moves - Equivalence of NFA’s with and without ε –
Moves.
Introduction
Definition of TOC
TOC describes the basic ideas and models underlying computing. TOC
suggests various abstract models of computation, represented mathematically.
History of Theory of Computation
1936 Alan Turing invented the Turing machine, and proved that there exists
an unsolvable problem.
1940’s Stored-program computers were built.
1943 McCulloch and Pitts invented finite automata.
1956 Kleene invented regular expressions and proved the equivalence of
regular expression and finite automata
1956 Chomsky defined Chomsky hierarchy, which organized languages
recognized by different automata into hierarchical classes.
1959 Rabin and Scott introduced nondeterministic finite automata and proved
its equivalence to (deterministic) finite automata.
1950’s-1960’s More works on languages, grammars, and compilers
1965 Hartmantis and Stearns defined time complexity, and Lewis, Hartmantis
and Stearns defined space complexity.
1971 Cook showed the first NP-complete problem, the satisfiability problem.
1972 Karp Showed many other NP-complete problems.
1976 Diffie and Helllman defined Modern Cryptography based on NPcomplete problems.
1978 Rivest, Shamir and Adelman proposed a public-key encryption scheme,
RSA.
Finite State systems
A finite automaton can also be thought of as the device shown below consisting of a tape
and a control circuit which satisfy the following conditions:
The tape has the left end and extends to the right without an end.
The tape is dividing into squares in each of which a symbol can be written prior to the
start of the operation of the automaton.
The tape has a read only head.
The head is always at the leftmost square at the beginning of the operation.
The head moves to the right one square every time it reads a symbol.
It never moves to the left. When it sees no symbol, it stops and the automaton
terminates its operation.
1 / 28

SITAMS – B.Tech – III Year - II Sem CSE
13CSE 321 – Theory of Computation
Dr. D. Jagadeesan, B.E., M.Tech., Ph.D.,
Professor in CSE,
Unit – I
There is a finite control which determines the state of the automaton and also controls
the movement of the head.
Basic Definitions
Symbol :
Symbol is a character.
Example : a,b,c,… , 0,1,2,3,….9 and special characters.
Alphabet :
An alphabet is a finite, nonempty set of symbol. It is denoted by ∑.
Example :
a) ∑ = {0,1}, the set of binary alphabet.
b) ∑ = {a,b……..z}, the set of all lowercase letters.
c) ∑ = {+, &,…..}, the set of all special characters.
String or Word :
A string is a finite set sequence of symbols chosen from some alphabets.
Example :
a) 0111010 is a string from the binary alphabet ∑ = {0,1}
b) aabbaacab is a string from the alphabet ∑ = {a,b,c}
Empty String :
The empty string is the string with zero occurrences of symbols (no symbols).
It is denoted by є.
Length of String :
The length of a string is number of symbols in the string. It denoted by |w|.
Example :
w = 010110101 from binary alphabet ∑ = {0,1}
Length of a string |w| = 9
2 / 28

SITAMS – B.Tech – III Year - II Sem CSE
13CSE 321 – Theory of Computation
Dr. D. Jagadeesan, B.E., M.Tech., Ph.D.,
Professor in CSE,
Unit – I
Power of an Alphabet:
If ∑ is an alphabet, we can express the set of all strings of certain length
from that alphabet by using an exponential notation. It is denoted by ∑k is
the set of strings of length k, each of whose symbols is in ∑.
Example :
∑ = {0,1} has 2 symbols
i) ∑1 = {0,1}
( 21 = 2)
ii) ∑2 = {00, 01, 10, 11} ( 22 = 4)
iii) ∑3 = {000,001,010,011,100,101,110,111} ( 23 = 8)
The set of strings over an alphabet ∑ is usually denoted by ∑*.
For instance, ∑* = {0,1}* = {є,0,1,00,01,10,11}
(∑*=∑0∑1∑2……) - with є symbol.
The set of strings over an alphabet ∑ excluding є is usually denoted by ∑+.
For instance, ∑+ = {0,1}+ = {0,1,00,01,10,11}
(∑+=∑*- {є} or ∑1∑2∑3…..…)
- without є symbol.
Concatenation of String
Join the two or more strings. Let x and y be two strings. Concatenation of
strings x and y is appending symbols of y to right end of x.
x = a1a2a3……………an and y = b1b2b3……………bn
Concatenation of String xy = a1a2a3……an b1b2b3….…bn
Example :
s = ababa
and
t = cdcddc
Concatenation st = ababacdcddc
Languages:
If Σ is an alphabet, and L Σ* then L is a language.
Examples:
o The set of legal English words
o The set of legal C programs
o The set of strings consisting of n 0's followed by n 1's
{ ϵ, 01,0011,000111, …}
Operations on Languages
Complementation
Let L be a language over an alphabet Σ. The complementation of L, denoted
byL, is Σ*–L.
Union
Let L1 and L2 be languages over an alphabet Σ. The union of L1 and L2,
denoted by L1L2, is {x | x is in L1 or L2}.
Intersection
Let L1 and L2 be languages over an alphabet Σ. The intersection of L1 and L2,
denoted by L1L2, is { x | x is in L1 and L2}.
3 / 28

SITAMS – B.Tech – III Year - II Sem CSE
13CSE 321 – Theory of Computation
Dr. D. Jagadeesan, B.E., M.Tech., Ph.D.,
Professor in CSE,
Unit – I
Concatenation
Let L1 and L2 be languages over an alphabet Σ. The concatenation of L1 and
L2, denoted by L1L2, is {w1w2| w1 is in L1 and w2 is in L2}.
Reversal
Let L be a language over an alphabet Σ. The reversal of L, denoted by Lr, is
{wr| w is in L}.
Kleene’s closure
Let L be a language over an alphabet Σ. The Kleene’s closure of L, denoted by
L*, is {x | for an integer n 0 x = x1 x2 … xn and x1, x2 , …, xn are in L}.
∞
*
L = U Li
(e.g. a* ={,a,aa,aaa,……})
i=0
Positive Closure
Let L be a language over an alphabet Σ. The closure of L, denoted by L+, is {
x |for an integer n 1, x = x1x2…xn and x1, x2 , …, xn are in L}
∞
+
L = U Li
(e.g. a* ={a,aa,aaa,……})
i=1
Finite Automaton
Automaton is an abstract computing device. It is a mathematical model of a system,
with discrete inputs, outputs, states and set of transitions from state to state that occurs on
input symbols from alphabet Σ.
It representations:
o Graphical (Transition Diagram or Transition Table)
o Tabular (Transition Table)
o Mathematical (Transition Function or Mapping Function)
Formal Definition of Finite Automata
A finite automaton is a 5-tuples; they are M=(Q, Σ, δ, q0, F)
where
Q is a finite set called the states
Σ is a finite set called the alphabet
δ : Q ×Σ → Q is the transition function
q0 ∈ Q is the start state also called initial state
F ⊆ Q is the set of accept states, also called the final states
Transition Diagram (Transition graph)
It is a directed graph associated with the vertices of the graph corresponds to
the states of the finite automata. (or) It is a 5-tuple graph used state and edges
represent the transitions from one state to other state.
1
Example: 0
1
1
q0
Start or Initial State
0
q1
qq22
Final or Accepting State
4 / 28

## Leave your Comments